In this task, I designed and implemented an interactive dashboard using Power BI (a Business Intelligence tool) to analyze a large dataset of Netflix Movies & TV Shows. The main goal of this exercise was to transform raw entertainment data into a visually engaging and business-friendly format that allows stakeholders to explore insights dynamically. Unlike static reports, this dashboard provided interactive capabilities such as filters, slicers, and drill-down features, enabling users to slice the data by multiple dimensions like release year, genres, ratings, and countries. By leveraging the visualization strengths of BI tools, I turned complex information into easy-to-understand visuals that highlight patterns, trends, and distributions in Netflix content.
- Imported the Netflix dataset into Power BI. -Cleaned and formatted key fields such as Title, Type (Movie/TV Show), Director, Release Year, Rating, and Genre.
- Ensured correct data types for smooth aggregation and filtering operations.
I created a series of dynamic and interactive charts:
- Total Summary Cards 🎯: Displayed overall counts for Movies (8,807), Directors (4,527), Genres (514), and the Time Range (1925–2021). These KPIs give users a quick snapshot of the dataset’s scope.
- Rating Distribution by TV Shows 📺: Visualized how Netflix categorizes its shows (TV-MA, TV-14, TV-PG, etc.). Helped in identifying the maturity level distribution of available content.
- Genres by Movies 🎬: Bar chart representation of popular genres like Drama, Documentaries, Comedies, and Stand-Up Comedy. Useful for understanding content diversity and consumer preferences.
- Country-Wise Ratings 🌍: Highlighted the number of titles produced across regions such as the United States, United Kingdom, Japan, South Korea, India, and Taiwan. Provided insights into regional contributions to Netflix’s library.
- Movies & TV Shows Breakdown 🥧: A pie chart showing the proportion of Movies (≈70%) vs TV Shows (≈30%). Quickly revealed Netflix’s strategic focus on movie content.
- Release Year Trends 📈: Line chart showcasing the distribution of releases over time. Identified peaks in content production, especially in the 2010s.
- Content Growth Over Time: The dataset shows a significant rise in content releases after 2010, aligning with Netflix’s global expansion.
- Genre Popularity: Dramas, Documentaries, and Comedies dominate, showing audience preference for storytelling and factual content.
- Regional Insights: The U.S. leads by a wide margin, but countries like India, South Korea, and Japan are emerging strongly.
- Content Type Ratio: Movies account for the majority of Netflix content, though TV Shows have grown steadily in recent years.
- Audience Ratings: The majority of Netflix’s catalog is rated TV-MA and TV-14, highlighting its focus on mature and young-adult audiences.
- Power BI → For creating dashboards and interactive visualizations.
- Data Cleaning & Transformation → Adjusted columns and handled categorical/numerical fields.
- DAX (Data Analysis Expressions) → Applied for calculated measures where needed.
- Visualization Components → Cards, Bar Charts, Pie Charts, Line Graphs, Filters, and Slicers.
- 📊 Dashboard Design Skills → Learned how to structure visuals for maximum clarity and storytelling impact.
- ⚡ Interactivity Mastery → Gained experience in implementing filters, slicers, and drill-downs for user-driven analysis.
- 🌍 Domain Insights → Understood global content patterns, genre popularity, and Netflix’s growth trends.
- 💡 Business Perspective → Learned how BI dashboards can help decision-makers quickly evaluate large datasets.
- 🧑💻 Practical BI Experience → Strengthened my hands-on expertise in Power BI, making me confident in building dashboards for real-world datasets.
The result of this task was a professional, interactive dashboard that transforms a massive dataset of Netflix content into an engaging and business-friendly format. By combining KPIs, charts, and slicers, I successfully built a tool that helps stakeholders explore what type of content Netflix produces, when it was released, which countries contribute the most, and which genres dominate the platform. This task not only boosted my technical skills in Power BI but also enhanced my ability to tell stories with data, turning raw numbers into insights that support strategic decision-making.
💼 Portfolio: https://linktr.ee/AbdullahUmar.DataAnalyst
📧 Email: umerabdullah048@gmail.com
Show what the Code and Output looks like.
